Stability of gene expression and epigenetic profiles highlights the utility of patient-derived paediatric acute lymphoblastic leukaemia xenografts for investigating molecular mechanisms of drug resistance

Abstract

Background: Patient-derived tumour xenografts are an attractive model for preclinical testing of anti-cancer drugs. Insights into tumour biology and biomarkers predictive of responses to chemotherapeutic drugs can also be gained from investigating xenograft models. As a first step towards examining the equivalence of epigenetic profiles between xenografts and primary tumours in paediatric leukaemia, we performed genome-scale DNA methylation and gene expression profiling on a panel of 10 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) tumours that were stratified by prednisolone response.

Results: We found high correlations in DNA methylation and gene expression profiles between matching primary and xenograft tumour samples with Pearson's correlation coefficients ranging between 0.85 and 0.98. In order to demonstrate the potential utility of epigenetic analyses in BCP-ALL xenografts, we identified DNA methylation biomarkers that correlated with prednisolone responsiveness of the original tumour samples. Differential methylation of CAPS2, ARHGAP21, ARX and HOXB6 were confirmed by locus specific analysis. We identified 20 genes showing an inverse relationship between DNA methylation and gene expression in association with prednisolone response. Pathway analysis of these genes implicated apoptosis, cell signalling and cell structure networks in prednisolone responsiveness.

Conclusions: The findings of this study confirm the stability of epigenetic and gene expression profiles of paediatric BCP-ALL propagated in mouse xenograft models. Further, our preliminary investigation of prednisolone sensitivity highlights the utility of mouse xenograft models for preclinical development of novel drug regimens with parallel investigation of underlying gene expression and epigenetic responses associated with novel drug responses.

Figure 1

Comparisons of DNA methylation and gene expression profiles between primary tumour tissue and xenografts. (A) Scatterplots of DNA methylation and gene expression array results from ALL26 showing high correlation between primary and xenograft tumours. (B) Heatmap plot of Pearson’s correlation coefficients of all primary and xenograft samples analysed for DNA methylation and gene expression. Coefficients greater than 0.94 and 0.84 between matching primary and xenograft tumours were observed for DNA methylation and gene expression respectively. (C) Heatmap plot of the most variable DNA methylation and gene expression probes. A high level of similarity between matching primary and xenograft tumours resulted in all pairs clustering together. Green Sample Bar depicts PPR, Blue sample Bar depicts PGR.

Figure 2

Heatmap plot of the most significant DNA methylation and gene expression probes distinguishing prednisolone good responders (PGR) from poor responders (PPR) after LIMMA analysis (BH adjusted p-value < 0.05). DNA methylation probes distinguished PGR from PPR while gene expression probes did not.

Figure 3

Scatterplot of the average DNA methylation and gene expression difference between PPR and PGR samples reveals 20 genes with a negative association between gene expression and DNA methylation.

Figure 4

Validation of DNA methylation across four probes, CAPS2, ARHGAP21, ARX and HOXB6 using SEQUENOM EpiTYPER chemistry.